@article {bnh-3436, title = {An Assessment of Pre- and Post Fire Near Surface Fuel Hazard in an Australian Dry Sclerophyll Forest Using Point Cloud Data Captured Using a Terrestrial Laser Scanner}, journal = {Remote Sensing}, volume = {8}, year = {2016}, month = {08/2016}, abstract = {

Assessment of ecological and structrual changes induced by fire events is important for understanding the effects of fire, and planning future ecological and risk mitigation strategies. This study employs Terrestrial Laser Scanning (TLS) data captured at multiple points in time to monitor the changes in a dry sclerophyll forest induced by a prescribed burn. Point cloud data was collected for two plots; one plot undergoing a fire treatment, and the second plot remaining untreated, thereby acting as the control. Data was collected at three epochs (pre-fire, two weeks post fire and two years post fire). Coregistration of these multitemporal point clouds to within an acceptable tolerance was achieved through a two step process utilising permanent infield markers and manually extracted stem objects as reference targets. Metrics describing fuel height and fuel fragmentation were extracted from the point clouds for direct comparison with industry standard visual assessments. Measurements describing the change (or lack thereof) in the control plot indicate that the method of data capture and coregistration were achieved with the required accuracy to monitor fire induced change. Results from the fire affected plot show that immediately post fire 67\% of area had been burnt with the average fuel height decreasing from 0.33 to 0.13 m. At two years post-fire the fuel remained signicantly lower (0.11 m) and more fragmented in comparison to pre-fire levels. Results in both the control and fire altered plot were comparable to synchronus onground visual assessment. The advantage of TLS over the visual assessment method is, however, demonstrated through the use of two physical and spatially quantifiable metrics to describe fuel change. These results highlight the capabilities of multitemporal TLS data for measuring and mapping changes in the three dimensional structure of vegetation. Metrics from point clouds can be derived to provide quantified estimates of surface and near-surface fuel loss and accumulation, and inform prescribed burn efficacy and burn severity reporting.

}, doi = {10.3390/rs8080679}, url = {http://www.mdpi.com/2072-4292/8/8/679}, author = {Luke Wallace and Vaibhav Gupta and Karin Reinke and Simon Jones} } @mastersthesis {bnh-6627, title = {Measuring fire-induced change in the understorey of an Australian dry sclerophyll forest using remote sensing}, year = {2016}, month = {08/2016}, school = {RMIT University}, address = {Melbourne}, abstract = {

This research investigates the use of remote sensing technologies for measuring and mapping the changes in the forest understorey in response to prescribed burning. Remote sensing has been used extensively to map the burn areas in fire-affected landscapes, but less work has been done focussing on beneath the canopy. Sub-canopy vegetation layers are important for habitat and for understanding the fuel hazards they may pose to the risk of wildfire. Accordingly, instruments and approaches must be able to perform in both pre- and post-burn environments, and be able to provide meaningful measures of change.

Wildfires are increasing in intensity and frequency, and in response prescribed burning is used to mitigate threats posed by them. Quantifying post-fire effects is important for burn severity, ecosystem recovery and post-fire hazard assessments. This information will allow land managers and scientists to understand fires in their environmental, economic and social contexts and help formulate responses and policies accordingly. However, measures of fire effects and fuel hazards which are done via visual assessments are known to be subjective and inconsistent between assessors and over time. What is needed is an improvement in the reporting procedures around quantification of fire effects which are both repeatable and quantifiable.

In this research two remote sensing technologies were used to measure, map and track changes in the understorey of an Australian dry sclerophyll forest. Terrestrial Laser Scanning (TLS) was used to derive vegetation structure variables and HSR (HyperSpectral Radiometry) was used to derive vegetation physiological variables. The study site was located in St. Andrews, Victoria, Australia within which a control plot and three fire treatment plots were set-up and monitored over a two year period, before and after a prescribed fire event conducted in autumn 2012. The datasets collected were used for statistical and spatial analysis of changes in understorey vegetation, and to assess those metrics best suited for describing different vegetation responses to fire effects.

The first part of this research examined the potential of TLS to detect fire-induced change in the forest understorey. From TLS point clouds a total of 18 metrics were extracted which were tested against accuracy and reliability criteria. Three metrics; mean AGHchange (Above Ground Height), median AGHchange and point countchange were shortlisted. To report different post-fire changes in burnt understorey, mean AGHchange metric was used. This metric was able to report fire effects such as total burn area, measures of patchiness, spatial distribution of burnt and unburnt areas, fuel accumulation and prescribed burn efficiency across various temporal scales.

The second part of this research analysed hyperspectral data of the near-surface (grass) and surface fuel layer (litter). Spectral changes in the near-surface fuel layer were observed in Visible (550nm), Near-Infrared (680-750nm) and Middle Infrared (970nm, 1220nm, 1550nm) domains of the electromagnetic spectrum. For the surface fuel layer (litter) changes were observed in the Middle Infrared domain (1140nm, 1225nm and 1700nm). The greatest difference from pre-burn levels for both the fuel layers occurred within the first two weeks post-burn. Spectral indices corresponding to the above determined broad spectral bands were tested to ascertain which were best at characterising burnt from unburnt targets whilst also tracking recovery. Indices such as NDVI, NBR and D720 were found to be the most suitable for near-surface fuel layer whilst D1230 for surface fuel layer.

A preliminary investigation into comparing the change detected by the two remote sensing technologies suggested that physiological change detected by HSR, recorded vegetation recovery as early as six weeks post-burn. Structural change detected by TLS even after two years post-burn was recorded as being close to two weeks post-burn levels. This finding matched well with visual assessments of structural measures (plant cover and height).

The findings of this study suggest that improvements in reporting procedures around quantification of fire effects can be achieved using TLS and HSR technology. TLS-derived structural metric, mean AGHchange can accurately detect quantified measures of fire-induced change in forest understorey that can be validated with field assessments. It can also report post-fire effects at various temporal scales including area burnt, burn patchiness, fuel load accumulation and prescribed burn efficiency. Spectral indices such as NDVI, NBR and D720 were able to accurately detect both vegetation loss and recovery. There is merit in further investigating TLS and HSR in conjunction for quantified and robust reporting of fire effects. The change detected by these technologies can be linked to inform both vegetation recovery and fuel accumulation.

}, keywords = {burn severity, fuel hazard, post-fire effects, prescribed burns, remote sensing}, url = {https://researchbank.rmit.edu.au/view/rmit:161758}, author = {Vaibhav Gupta} } @article {bnh-1893, title = {Assessing Metrics for Estimating Fire Induced Change in the Forest Understorey Structure Using Terrestrial Laser Scanning}, journal = {Remote Sensing}, volume = {7}, year = {2015}, month = {06/2015}, pages = {8180-8201}, chapter = {8180}, abstract = {

Quantifying post-fire effects in a forested landscape is important to ascertain burn severity, ecosystem recovery and post-fire hazard assessments and mitigation planning. Reporting of such post-fire effects assumes significance in fire-prone countries such as USA, Australia, Spain, Greece and Portugal where prescribed burns are routinely carried out. This paper describes the use of Terrestrial Laser Scanning (TLS) to estimate and map change in the forest understorey following a prescribed burn. Eighteen descriptive metrics are derived from bi-temporal TLS which are used to analyse and visualise change in a control and fire-altered plot. Metrics derived are Above Ground Height-based (AGH) percentiles and heights, point count and mean intensity. Metrics such as\ AGH50change,\ mean AGHchange\ and\ point countchange\ are sensitive enough to detect subtle fire-induced change (28\%{\textendash}52\%) whilst observing little or no change in the control plot (0{\textendash}4\%). A qualitative examination with field measurements of the spatial distribution of burnt areas and percentage area burnt also show similar patterns. This study is novel in that it examines the behaviour of TLS metrics for estimating and mapping fire induced change in understorey structure in a single-scan mode with a minimal fixed reference system. Further, the TLS-derived metrics can be used to produce high resolution maps of change in the understorey landscape

}, keywords = {Terrestrial LiDAR; change detection; understorey; prescribed burns; terrestrial laser scanning; single-scan; LiDAR metrics}, doi = {10.3390/rs70608180}, url = {http://www.mdpi.com/2072-4292/7/6/8180}, author = {Vaibhav Gupta and Karin Reinke and Simon Jones and Luke Wallace and Lucas Holden} }